Yeying Zhu

Assistant Professor

Yeying ZhuContact Information:
Yeying Zhu

Yeying Zhu's personal website

Research interests

My research interest lies in causal inference, machine learning and the interface between the two. My current work focuses on the inverse weighted estimation of causal effects using propensity scores and marginal structural models.

The objective is to develop innovative machine learning algorithms for the modeling of propensity scores for both binary and continuous treatments. I am also working on the development of model averaging methods to deal with extreme weights, which is a common problem faced by data analysts while using inverse probability weighting. Meanwhile, I am working on causal mediation analysis, which examines how one variable is causally related to the other variable through one/multiple intermediate variables.

The application of my work mostly lies in medical studies, public health sciences and other social sciences. My other research areas include variable selection and high-dimensional data. 

Education/biography

Professor Zhu received her BSc in Statistics at East China Normal University in 2006. Then, she went to National University of Singapore for her master degree and later, joined Penn State University in 2008. She graduated with a PhD degree in 2013. She was a pre-doctoral fellow at the Quantitative Social Science Initiative (QuaSSI) between 2010 and 2011 and a research assistant at the Penn State Methodology Center between 2011 and 2013.

Affiliation: 
University of Waterloo
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